Regulation of the unfolded protein response transducer IRE1α by SERPINH1 aggravates periodontitis with diabetes mellitus via prolonged ER stress

Li, Mengdi; Huang, Shuheng; Zhang, Yong; Song, Zhenyuan; Fu, Haijun; Lin, Zhengmei; Huang, Xiaohong

doi:10.1016/j.cellsig.2022.110241

Cited by 7 publications

(5 citation statements)

References 53 publications

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“…This study indicated that enriched genes might play important role in PCOS. As previously reported, FOXP3 [446], TIMP4 [447], OAS3 [448], SOCS1 [128], CD74 [129], PLK1 [449], TGFB1 [450], RAPGEF1 [451], SERPINH1 [452], ATF5 [66], GATA6 [133], IGF2BP1 [453], IRX3 [454], FOXC2 [455], SNHG17 [456], TAF1C [457], HHIP (hedgehog interacting protein) [458], POMC (proopiomelanocortin) [459], DOK5 [76], COL1A1 [460], POSTN (periostin) [461], SOD3 [462], ADAMTS13 [463], FABP5 [464], MAPK11 [465], KCTD15 [83], HSPG2 [466], MST1 [467], MGAT2 [468], LGR5 [469], SPINK1 [470], CYP19A1 [471], PLAC8 [90], CD36 [472], AQP5 [473], GIPR (gastric inhibitory polypeptide receptor) [474], ARG1 [475], SORL1 [476], CD4 [477], F11R [478], LEPR (leptin receptor) [479], CDH13 [480], AR (androgen receptor) [481], FOXO1 [102], MALT1 [482], PAM (peptidylglycine alpha-amidating monooxygenase) [483], B2M [484], TCF4 [485], CAV2 [486], HSBP1 [487], COLEC12 [488], ADRA2A [489], SLC38A4 [490], TM6SF2 [491], GLP2R [111], KLB (klotho beta) [492], NFAT5 [493], PON2 [494], ZMAT3 [495], DST (dystonin) [426], MGST3 [496], COQ2 [118], EPHX2 [497], C2 [181] and FAM3C [120] are altered expression in type 2 diabetes mellitus. Previous studies have shown that DRD4 [498], TIMP4 [499], SOCS1 [500], CD74 [501], TGFB1 [502], ACTG2 [503], ISG15 [504], HOXC8 [...…”

Section: Discussionmentioning

confidence: 85%

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Vastrad¹,

Vastrad²

2023

Preprint

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Polycystic ovary syndrome (PCOS) is is associated with infertility, obesity, insulin resistance, hyperinsulinemia, type 2 diabetes mellitus, hypertension, cardiovascular problems, neurological and psychological problems and cancer. The specific mechanism of PCOS and its complications remains unclear. The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of PCOS and its complications. The next generation squancing (NGS) datset GSE199225 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. A protein-protein interaction (PPI) network was constructed and module analysis was performed using HiPPIE and cytoscape. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were also constructed for research. The expression of the hub genes was validated using receiver operating characteristic (ROC) curve analysis. We have identified 957 DEGs in total, including 478 up regulated genes and 479 down regulated gene. GO and REACTOME illustrated that DEGs in PCOS were significantly enriched in regulation of molecular function, developmental process, interferon signaling and platelet activation, signaling and aggregation. Finally, through analyzing the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, we screened hub genes HSPA5, PLK1, RIN3, DBN1, CCDC85B, DISC1, AR, MTUS2, LYN and TCF4 by the Cytoscape software. This study uses a series of bioinformatics technologies to obtain hug genes and key pathways related to PCOS and its complications. These analysis results provide us with novel ideas for finding biomarkers and treatment methods for PCOS and its complications.

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Section: Discussionmentioning

confidence: 85%

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Vastrad¹,

Vastrad²

2023

Preprint

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“…S5A, Additional file 16 : Table S1, Additional file 4 ). In the stromal compartment, when compared to the water control, Metformin significantly upregulated Angptl1 (a glycoprotein shown to inhibit osteoclast formation and osteoblastic differentiation [ 46 ]), Ifitm3 (involved in immune response or antiviral activity [ 47 ]), Ncp2 (a gene encoding a protein responsible for cholesterol binding, shown to be important in periodontal tissues homeostasis [ 48 ]), and Serpinh1 (a controller of endoplasmic reticulum stress, responsible for maintaining cell homeostasis under high glucose stress [ 49 ]) (Additional file 13 : Fig. S6A, Additional file 16 : Table S1, Additional file 5 ).…”

Section: Resultsmentioning

confidence: 99%

Repurposing Metformin for periodontal disease management as a form of oral-systemic preventive medicine

Neves,

Satie Okajima,

Elbahtety

et al. 2023

J Transl Med

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Background Despite the improvements in treatment over the last decades, periodontal disease (PD) affects millions of people around the world and the only treatment available is based on controlling microbial load. Diabetes is known to increase the risk of PD establishment and progression, and recently, glucose metabolism modulation by pharmaceutical or dietarian means has been emphasised as a significant modulator of non-communicable disease development. Methods The impact of pharmaceutically controlling glucose metabolism in non-diabetic animals and humans (REBEC, UTN code: U1111-1276-1942) was investigated by repurposing Metformin, as a mean to manage periodontal disease and its associated systemic risk factors. Results We found that glucose metabolism control via use of Metformin aimed at PD management resulted in significant prevention of bone loss during induced periodontal disease and age-related bone loss in vivo. Metformin also influenced the bacterial species present in the oral environment and impacted the metabolic epithelial and stromal responses to bacterial dysbiosis at a single cell level. Systemically, Metformin controlled blood glucose levels and age-related weight gain when used long-term. Translationally, our pilot randomized control trial indicated that systemic Metformin was safe to use in non-diabetic patients and affected the periodontal tissues. During the medication window, patients showed stable levels of systemic blood glucose, lower circulating hsCRP and lower insulin levels after periodontal treatment when compared to placebo. Finally, patients treated with Metformin had improved periodontal parameters when compared to placebo treated patients. Conclusion This is the first study to demonstrate that systemic interventions using Metformin in non-diabetic individuals aimed at PD prevention have oral-systemic effects constituting a possible novel form of preventive medicine for oral-systemic disease management.

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“…Limited studies showed a greater expression of IRE1α and glucose‐regulating protein 78 (GRP78) in the human periodontium of individuals with periodontitis, while a lower expression in periodontitis with diabetes, indicating damaged ER compensatory response in periodontitis with diabetes 34 . However, this result was inconsistent with that of the study by Tan et al., which showed higher GRP78 levels in periodontitis patients with diabetes 35 .…”

Section: Lipotoxicity Mediates the Detrimental Effects Of Diabetes On...mentioning

confidence: 89%

“…Proved/potential mechanisms that mediate the detrimental effects of lipotoxicity on diabetes-associated periodontitis. M: Greater ROS levels and oxidative stress markers in crevicular fluid 20,23,26,27 M: Impaired mitochondrial function in periodontium cells 24 M: Lower Nrf2 level in periodontal tissues 24,25 O: Increased PDLSCs apoptosis, 24 senescence and telomere dysfunction 23 O: Increased bone resorption [23][24][25] Clinical 19,20,26,27 In vivo 21,22,24 In vitro 21,[23][24][25] ER stress M: Greater UPR-related gene expression and impaired ER function in periodontal tissues [36][37][38]108 In vivo 34,35,37,38,108 In vitro 34,36 Inflammation M: Inflammatory destruction of the supporting tissues around the teeth and an aberrant host response 39 M: Greater IL-1β and IL-18 in the gingival crevicular fluid and the activation of NLRP3 in gingival tissue 40 M: Greater expression of CD36 in macrophages and gingival fibroblasts a46-48 O: Increased osteoclast formation and inflammatory cytokine production a47-51 O: Increased bone resorption 47,48,50 Clinical 40,47 In vivo 39,46,49,…”

Section: Ta B L Ementioning

confidence: 99%

Lipotoxicity: The missing link between diabetes and periodontitis?

Sun,

Yin,

Yang

et al. 2024

J of Periodontal Research

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Lipotoxicity refers to the accumulation of lipids in tissues other than adipose tissue (body fat). It is one of the major pathophysiological mechanisms responsible for the progression of diabetes complications such as non‐alcoholic fatty liver disease and diabetic nephropathy. Accumulating evidence indicates that lipotoxicity also contributes significantly to the toxic effects of diabetes on periodontitis. Therefore, we reviewed the current in vivo, in vitro, and clinical evidence of the detrimental effects of lipotoxicity on periodontitis, focusing on its molecular mechanisms, especially oxidative and endoplasmic reticulum stress, inflammation, ceramides, adipokines, and programmed cell death pathways. By elucidating potential therapeutic strategies targeting lipotoxicity and describing their associated mechanisms and clinical outcomes, including metformin, statins, liraglutide, adiponectin, and omega‐3 PUFA, this review seeks to provide a more comprehensive and effective treatment framework against diabetes‐associated periodontitis. Furthermore, the challenges and future research directions are proposed, aiming to contribute to a more profound understanding of the impact of lipotoxicity on periodontitis.

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Regulation of the unfolded protein response transducer IRE1α by SERPINH1 aggravates periodontitis with diabetes mellitus via prolonged ER stress

Cited by 7 publications

References 53 publications

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Repurposing Metformin for periodontal disease management as a form of oral-systemic preventive medicine

Lipotoxicity: The missing link between diabetes and periodontitis?

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